<?php
/*
 * @ https://EasyToYou.eu - IonCube v11 Decoder Online
 * @ PHP 7.2 & 7.3
 * @ Decoder version: 1.1.6
 * @ Release: 10/08/2022
 */

// Decoded file for php version 71.
require_once PHPEXCEL_ROOT . "PHPExcel/Shared/trend/bestFitClass.php";
require_once PHPEXCEL_ROOT . "PHPExcel/Shared/JAMA/Matrix.php";
class PHPExcel_Polynomial_Best_Fit extends PHPExcel_Best_Fit
{
    protected $bestFitType = "polynomial";
    protected $order = 0;
    public function getOrder()
    {
        return $this->order;
    }
    public function getValueOfYForX($xValue)
    {
        $retVal = $this->getIntersect();
        $slope = $this->getSlope();
        foreach ($slope as $key => $value) {
            if($value != 0) {
                $retVal += $value * pow($xValue, $key + 1);
            }
        }
        return $retVal;
    }
    public function getValueOfXForY($yValue)
    {
        return ($yValue - $this->getIntersect()) / $this->getSlope();
    }
    public function getEquation($dp = 0)
    {
        $slope = $this->getSlope($dp);
        $intersect = $this->getIntersect($dp);
        $equation = "Y = " . $intersect;
        foreach ($slope as $key => $value) {
            if($value != 0) {
                $equation .= " + " . $value . " * X";
                if(0 < $key) {
                    $equation .= "^" . ($key + 1);
                }
            }
        }
        return $equation;
    }
    public function getSlope($dp = 0)
    {
        if($dp != 0) {
            $coefficients = [];
            foreach ($this->_slope as $coefficient) {
                $coefficients[] = round($coefficient, $dp);
            }
            return $coefficients;
        } else {
            return $this->_slope;
        }
    }
    public function getCoefficients($dp = 0)
    {
        return array_merge([$this->getIntersect($dp)], $this->getSlope($dp));
    }
    private function polynomialRegression($order, $yValues, $xValues, $const)
    {
        $x_sum = array_sum($xValues);
        $y_sum = array_sum($yValues);
        $xx_sum = $xy_sum = 0;
        for ($i = 0; $i < $this->valueCount; $i++) {
            $xy_sum += $xValues[$i] * $yValues[$i];
            $xx_sum += $xValues[$i] * $xValues[$i];
            $yy_sum += $yValues[$i] * $yValues[$i];
        }
        for ($i = 0; $i < $this->valueCount; $i++) {
            for ($j = 0; $j <= $order; $j++) {
                $A[$i][$j] = pow($xValues[$i], $j);
            }
        }
        for ($i = 0; $i < $this->valueCount; $i++) {
            $B[$i] = [$yValues[$i]];
        }
        $matrixA = new Matrix($A);
        $matrixB = new Matrix($B);
        $C = $matrixA->solve($matrixB);
        $coefficients = [];
        for ($i = 0; $i < $C->m; $i++) {
            $r = $C->get($i, 0);
            if(abs($r) <= pow(10, -9)) {
                $r = 0;
            }
            $coefficients[] = $r;
        }
        $this->intersect = array_shift($coefficients);
        $this->_slope = $coefficients;
        $this->calculateGoodnessOfFit($x_sum, $y_sum, $xx_sum, $yy_sum, $xy_sum);
        foreach ($this->xValues as $xKey => $xValue) {
            $this->yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);
        }
    }
    public function __construct($order, $yValues, $xValues = [], $const = true)
    {
        if(parent::__construct($yValues, $xValues) !== false) {
            if($order < $this->valueCount) {
                $this->bestFitType .= "_" . $order;
                $this->order = $order;
                $this->polynomialRegression($order, $yValues, $xValues, $const);
                if($this->getGoodnessOfFit() < 0 || 0 < $this->getGoodnessOfFit()) {
                    $this->_error = true;
                }
            } else {
                $this->_error = true;
            }
        }
    }
}

?>